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CeDRI at eRisk 2021: a naive approach to early detection of psychological disorders in social media
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Advisor(s)
Abstract(s)
This paper describes the participation of the CeDRI team in eRisk 2021 tasks, particularly, the Task 1: Early Detection of Signs of Pathological Gambling and Task 2: Early Detection of Signs of Self-Harm. The main difference between these two is that the first is a “test only” challenge, where no training data is supplied. The second task has labeled data available, which can be used for training. Both tasks were addressed using the same algorithms, using a custom training set for Task 1 and the provided data in the second. The algorithms were TfIdf vectorizer with a Logistic Regression layer, Word2Vec vectorizer with LSTM and Word2Vec vectorizer with CNN. All vectorizers and Neural Networks were trained solely with the training data. As expected, the algorithms did not state-of-the-art, but the experience allowed to reflect in several aspects related to the importance of proper dataset preparation and processing. © 2021 Copyright for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).
Description
Keywords
Early risk detection Tf-Idf Word2Vec Recursive neural networks Dataset heuristics DL4J
Pedagogical Context
Citation
Lopes, Rui Pedro (2021). CeDRI at eRisk 2021: a naive approach to early detection of psychological disorders in social media. In CEUR Workshop Proceedings. Bucharest, Romania. p. 981-991
Publisher
CEUR Workshop Proceedings